molfeat - Featurize molecules for machine learning
Converts SMILES strings or RDKit molecules into fingerprints, descriptors, and pretrained embeddings for molecular machine learning.
Tags
Updated: 2026-09-28Capabilities
Typical Inputs
Typical Outputs
What this skill does
- Convert molecules to features
- Compute molecular fingerprints
- Generate molecular descriptors
- Extract pretrained embeddings
- Process molecular batches
- Cache featurization results
- Save transformer configurations
- Load transformer configurations
- Discover available featurizers
Inputs
- SMILES strings
- RDKit molecules
- Featurizer configuration
- Molecular datasets
- Pretrained model names
- Configuration file paths
Outputs
- Feature vectors
- Feature matrices
- Pretrained embeddings
- Saved YAML configurations
- Featurizer listings
- Error logs
Requirements
- Python environment
- Installed molfeat package
- Optional featurizer dependencies
- Compatible pretrained model support